qrisp.QuantumCircuit.get_unitary#

QuantumCircuit.get_unitary(decimals: int | None = None) → ndarray[source]#

Return the unitary matrix of this QuantumCircuit as a NumPy array.

Works with both numeric and abstract (SymPy) parameters. When the circuit contains symbolic parameters, the returned array has dtype=object with SymPy expressions as entries.

Parameters:

decimalsint, optional: Number of decimal places to round to. When not provided, full precision is returned. For symbolic arrays, floating-point coefficients inside each expression are rounded. Values within 10**(-decimals) of 1 are snapped to exactly 1 to suppress floating-point noise.

Returns:

numpy.ndarray: The unitary matrix. dtype is complex64 for numeric circuits and object for symbolic ones.

Examples

We synthesize a controlled phase gate and inspect the unitary:

>>> from qrisp import QuantumCircuit
>>> import numpy as np
>>> qc = QuantumCircuit(2)
>>> phi = np.pi
>>> qc.p(phi/2, 0)
>>> qc.p(phi/2, 1)
>>> qc.cx(0,1)
>>> qc.p(-phi/2, 1)
>>> qc.cx(0,1)
>>> qc.get_unitary(decimals = 4)
array([[ 1.+0.j,  0.+0.j,  0.+0.j,  0.+0.j],
       [ 0.+0.j,  1.+0.j,  0.+0.j,  0.+0.j],
       [ 0.+0.j,  0.+0.j,  1.+0.j,  0.+0.j],
       [ 0.+0.j,  0.+0.j,  0.+0.j, -1.+0.j]], dtype=complex64)

We now synthesize the exact same QuantumCircuit, but this time phi is a SymPy symbol.

>>> from sympy import Symbol
>>> qc = QuantumCircuit(2)
>>> phi = Symbol("phi")
>>> qc.p(phi/2, 0)
>>> qc.p(phi/2, 1)
>>> qc.cx(0,1)
>>> qc.p(-phi/2, 1)
>>> qc.cx(0,1)
>>> qc.get_unitary(decimals = 4)
array([[1, 0, 0, 0],
       [0, 1, 0, 0],
       [0, 0, 1, 0],
       [0, 0, 0, exp(I*phi)]], dtype=object)